4 Machine Learning Platforms for Effective Predictive Analytics

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4 Machine Learning Platforms for Effective
Predictive Analytics
With every passing year, the technology sector
experiences the influx of a new buzzword. With
this growing influx, tech leaders across the
globe must keep their businesses ready to adapt
and improvise their existing environment to cope
up with evolving technology. One such technology
that is revolutionizing the business world is
machine learning. The technology allows
businesses to create several models such as
predictive analytics and prescriptive analytics.
However, the major challenge that every
organization must consider is which machine
learning platform will be the best for their
business? So, lets have a look Predictive
Analytics at the Forefront of Business
Growth Today almost every organization looks for
predictive analytics capabilities. This results
in the growing interest in technologies such as
Big Data and artificial intelligence. According
to some surveys, approximately 90 of companies
believe predictive analytics is an essential
asset for their business growth. However, there
are only a few respondents who have put
predictive analytics to the implementation. So
how has predictive analytics become so
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• demanding? What are the advantages it offers to
  your business? And what are the best predictive
  analytics tools that can help your business stay
  ahead of the competition?
• Now lets have a look at some of the machine
  learning platforms that can help organizations
• to have effective predictive analytics for their
  business.
• RapidMiner Studio
• RapidMiner delivers a unique combination of data
  analytics and custom business development. The
  tool is known as code-optional businesses can
  perform their task quickly with reusable codes.
  The essential feature of this predictive
  analytics tool is that it allows the
  organizations to automate the reporting process
  based on time, or channels, which can be
  triggered using a user-friendly dashboard. The
  tool enables businesses to import their data
  sets to the existing environment and export the
  same data sets to other programs using its 60
  native integrations.
• Databricks Machine Learning Runtime
• Databricks MLFlow is an open-source machine
  learning platform that allows organizations to
  monitor and manage the entire machine learning
  lifecycles. The platform allows the
  organizations to run experiments with any ML
  library, framework, or language, and
  automatically keep track of parameters, metrics,
  code, and models from each experiment. Moreover,
  it also allows businesses to discover, and move
  the machine learning models such as predictive
  analytics from experimenting to online testing
  and production.
• Microsoft Azure Machine Learning
• Azure Machine Learning is a cloud platform that
  allows developers to build, train, and deploy AI
  and predictive analytics models. Microsoft is
  persistently making improvements to its machine
  learning platform to allow the platform to add
  new functionalities and features. The company
  has recently announced changes to Azure Machine
  Learning. These changes include, open data sets,
  improved visual interface, automated ML-UX, and
  Data Box with FPGA.
• Jupyter Notebook
• Jupyter notebook is one of the most extensively
  used open-source machine learning platforms
  globally. The platform provides speed and
  accuracy in terms of processing and data
  monitoring. Since the platform supports three
  languages viz. Julia, Python, and R, it becomes
  easy for data scientists to create predictive
  analytics models from the data collected from
  various sources. Moreover, the platform allows
  the users to store and share live codes in the
  form of notebooks.
• Lets have a look at the questions mentioned
  above.

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• Client Success Story
• How we improved clients lead acquisition and
• conversion rate with AI?
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• How Predictive Analytics Has Become a
  Must-to-Have Functionality for Organizations?
• According to a report by Allied Market Research,
  the predictive analytics market was estimated to
  be around US 7.32 billion in 2019. This market
  is projected to surpass the value of US 35.45
  billion by the end of 2027. The report also
  states that the market is projected to witness a
  21.9 CAGR during the forecast period of 2020 to
  2027. The markets growth is the attribute of
  raising awareness of the large data volume
  amongst the organizations. Moreover, the race of
  gathering, processing, and monitoring the data to
  deduce a sustainable outcome for the customer
  has led to the growth in the demand for
  predictive analytics in various organizations.
• What are the Advantages of Using Predictive
  Analytics?
• Avoids Customer Rotation and Reduce Customer
  Churn
• Predictive analytics allows organizations to
  create customer segments about loss risks. The
  segment includes both major and minor risks. Once
  the segments are made, the data engineers can
  apply corrective actions promptly that can reduce
  the dissatisfaction among the customers and
  further diminish the risk of customer churn.
• Better Campaign Planning
• The predictive analytics solutions allow the
  organizations to analyze the behavior, pattern,
  interactions, and web browsing of the customers.
  This allows the businesses to develop an
  actionable plan that helps them to attract more
  prospects. Moreover, the solutions also enable
  the companies to define the best time and channel
  to communicate with the customers, enhancing
  their campaigns effectiveness.
• Improved Sales Probability

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customers in different mediums efficiently.
Predictive analytics suggests practical ways to
attract customers and develop sales plans
according to their purchase patterns. 4.
Personalized Services Long gone are the days
when the one-size-fits-for-all approach worked
for the businesses. Today, customers are looking
for companies that can offer services that are
oriented towards their requirements. Predictive
analytics and other data platform management
services allow companies to gather information
about their customers expectations. This will
enable them to treat their customers uniquely,
providing a personalized customer experience.
This, as a result, helps the businesses to
generate better leads and gain more profit. To
Sum Up The businesses have transformed their
operations from old brick and mortars to digital
landscapes. They are using new techniques and
technologies that can attract more customers to
their business. To achieve this task, the
organizations implement predictive analytics to
their operations to gain a competitive edge over
their competitors. If you are looking for
someone who can help you formulate an effective
strategy for predictive analytics, we can help.
Connect with us.